AIMC Topic: Transcriptome

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Identification and experimental validation of diagnostic and prognostic genes CX3CR1, PID1 and PTGDS in sepsis and ARDS using bulk and single-cell transcriptomic analysis and machine learning.

Frontiers in immunology
BACKGROUND: Sepsis is an uncontrolled reaction to infection that causes severe organ dysfunction and is a primary cause of ARDS. Patients suffering both sepsis and ARDS have a poor prognosis and high mortality. However, the mechanisms behind their si...

Machine learning analysis of CD4+ T cell gene expression in diverse diseases: insights from cancer, metabolic, respiratory, and digestive disorders.

Cancer genetics
CD4 T cells play a pivotal role in the immune system, particularly in adaptive immunity, by orchestrating and enhancing immune responses. CD4 T cell-related immune responses exhibit diverse characteristics in different diseases. This study utilizes g...

Comparative transcriptomic and molecular biology analyses to explore potential immune responses to challenge in .

Frontiers in cellular and infection microbiology
is a significant pathogen affecting shrimp and crab farming, particularly strains carrying genes associated with acute hepatopancreatic necrosis syndrome. However, the immune response of to infection remains unclear. To address this knowledge gap,...

Spatially-resolved analyses of muscle invasive bladder cancer microenvironment unveil a distinct fibroblast cluster associated with prognosis.

Frontiers in immunology
BACKGROUND: Muscle-invasive bladder cancer (MIBC) is a prevalent cancer characterized by molecular and clinical heterogeneity. Assessing the spatial heterogeneity of the MIBC microenvironment is crucial to understand its clinical significance.

Identification and validation of susceptibility modules and hub genes in polyarticular juvenile idiopathic arthritis using WGCNA and machine learning.

Autoimmunity
BACKGROUND: Juvenile idiopathic arthritis (JIA), superseding juvenile rheumatoid arthritis (JRA), is a chronic autoimmune disease affecting children and characterized by various types of childhood arthritis. JIA manifests clinically with joint inflam...

Exploring tumor microenvironment interactions and apoptosis pathways in NSCLC through spatial transcriptomics and machine learning.

Cellular oncology (Dordrecht, Netherlands)
BACKGROUND: The most common type of lung cancer is non-small cell lung cancer (NSCLC), accounting for 85% of all cases. Programmed cell death (PCD), an important regulatory mechanism for cell survival and homeostasis, has become increasingly prominen...

Identification and validation of the diagnostic biomarker MFAP5 for CAVD with type 2 diabetes by bioinformatics analysis.

Frontiers in immunology
INTRODUCTION: Calcific aortic valve disease (CAVD) is increasingly prevalent among the aging population, and there is a notable lack of drug therapies. Consequently, identifying novel drug targets will be of utmost importance. Given that type 2 diabe...

Recognizing SARS-CoV-2 infection of nasopharyngeal tissue at the single-cell level by machine learning method.

Molecular immunology
SARS-CoV-2 has posed serious global health challenges not only because of the high degree of virus transmissibility but also due to its severe effects on the respiratory system, such as inducing changes in multiple organs through the ACE2 receptor. T...

Deep profiling of gene expression across 18 human cancers.

Nature biomedical engineering
Clinical and biological information in large datasets of gene expression across cancers could be tapped with unsupervised deep learning. However, difficulties associated with biological interpretability and methodological robustness have made this im...

Identification and validation of the nicotine metabolism-related signature of bladder cancer by bioinformatics and machine learning.

Frontiers in immunology
BACKGROUND: Several studies indicate that smoking is one of the major risk factors for bladder cancer. Nicotine and its metabolites, the main components of tobacco, have been found to be strongly linked to the occurrence and progression of bladder ca...